tbuckley/cabot-search huggingface dataset:
Liquidscan mediated HER2 amplification detection in patient samples study.
Authors: Rolf Muller, Kay Yeung, Stephenie Jones, Christopher Brandt, Vincent Anthony Funari, Sally Agersborg, Judy Muller-Cohn, Janet Dickerson
Journal: Journal of Clinical Oncology (2022)

e13016 Background: Overexpression of HER2 serves as an oncogenic driver in breast cancer which can result in tumor progression and distant metastases. Amplification or overexpression of HER2 occurs in approximately 15–30% of breast cancers and serves as a therapeutic, prognostic and predictive biomarker. There have been tremendous advances in HER2+ breast cancer management and there is an need to identify patients with HER2+ early breast cancer who may benefit from de-escalation or escalation of treatment. In addition, selection of HER2 therapies beyond the 2 nd line setting for HER2+ metastatic breast cancer is currently unclear. Therefore, rapid monitoring tests for treatment response are needed. Liquid biopsy may provide a cost effective, sensitive, and non-invasive approach to monitor response. Methods: Whole blood (8ml) from 20 consenting patients with confirmed stage 3 or 4 metastatic breast cancer with clinical Her2 status identified by solid tissue biopsy (10 HER2+ and 10 HER2-) were collected. Circulating tumor cells were isolated on the LiquidScan system, were probed by HER2 FISH, analyzed using automated and visual microscopy. Results: Protocols were optimized to obtain morphology and cellularity of the tumor cells allowing conclusive HER2 identification for all samples. All samples from patients identified as Her2+ by standard invasive solid tumor biopsies could be identified (100% concordance), whereas for one sample that was reported as HER2-, cells were identified with the liquid biopsy having HER2+ FISH morphology. Further molecular analysis on this patient is under way. Conclusions: We were able to demonstrate that non-invasive liquid biopsy with the LiquidScan identifies HER2 status. The method has high concordance with conventional solid biopsy approach and may be a promising for patient monitoring. We will expand to larger sample sets to explore the full capacity of liquid biopsy to monitor and diagnose HER2 related diseases.
Assessing the landscape in medical oncology medical education scholarship: A scoping study.
Authors: Ruijia Jin, Sean McKay Fenlon Addison, Vanessa Kitchin, Daniel W. Golden, Vincent C. Tam, Paris-Ann Ingledew
Journal: Journal of Clinical Oncology (2022)

11009 Background: Medical oncology and medical education have both expanded exponentially over the past 50 years; as such, it is important to understand the current status of postgraduate medical oncology education and develop ways to advance this field. This study undertakes a scoping review of medical education literature in medical oncology to inform future scholarship in this area. Methods: MEDLINE (Ovid), Embase (Ovid), ERIC (EBSCO), and Web of Science (UBC Core Collection) were searched to find peer-reviewed English language articles on Postgraduate Medical Education in Medical Oncology published between 2009 and 2020. The review was designed in accordance with updated methodological guidance for the conduct of scoping review. Articles were classified by learning specialty, learner training level, region of authorship, single or multi-institution, year of publication, whether the journal was an education journal, quantitative vs qualitative design, study methodology, and category or topic. A modified Kerns framework for curriculum development was used to assess the type of curriculum intervention, Boyer’s definition of scholarship was used to classify the type of scholarship, and the CanMEDS Framework was used to map the domains of physician competency each study aims to address. Results were interpreted using descriptive statistics and collated and summarized utilizing predetermined conceptual frameworks. Results: 2959 references were initially found across the 4 databases. After title and abstract screening, 305 articles remained; after full text review, a total of 144 articles were included in our final analysis. These data showed that postgraduate medical oncology graduate medical education scholarship is increasing and most commonly observed in the United States. Quantitative studies were most common with surveys used as the most popular study approach. In terms of CanMEDS framework, Professional and Medical Expert comprised the large majority of education focuses, while very few articles addressed Leader or Health Advocate. Curriculum development, professional development, and attitudinal skills (communication skills, ethics) were the dominant research themes, while no articles discussed teacher training. Conclusions: By investigating the body of current literature, this research identifies areas of highest priority in postgraduate medical oncology graduate medical education and opportunities for growth. Whereas areas like professionalism and attitudinal skills are well-studied, research is lacking in leadership, health advocacy and teaching training. This study provides guidance for future medical education scholarship in medical oncology and establishes a benchmark to examine changes in medical oncology educational scholarship over time.
Molecular alterations detected on patients with glioblastoma and low-grade glioma: Review of 37 cases.
Authors: Kristi Beshiri, Nicolas Epaillard, Arnaud Bayle, Capucine Baldini, Sarah Naomie Dumont
Journal: Journal of Clinical Oncology (2022)

e15030 Background: Glioblastoma (GBM) is a short term life-threatening tumor, while lower-grade glioma (LGG) is a heterogeneous entity with longer survival due to its natural history. As few therapeutic options emerged in the past decades, innovation is lead by targetable molecular alterations such as FGFR, BRAF, NTRK... Therefore, molecular profiling access is critical for patients. Methods: We collected data from patients with GBM and LGG whose tumor sample underwent a molecular profiling with Foundation Medicine FMI testing trough clinical trials. Results: In the GBM group, we identified 26 patients, 18 males and 8 females. Medium age was 47. Median OS was 20.3 months (IC 95% 14.3-26.2). All patients were IDH wide type, one had a methylated MGMT with 13 unknown. Among them, we identified 126 alterations. The most frequent were: AKT (15.4%), BARD1 (15.4%), CDKN2A (28.5%), CDKN2B (42.3%), CKDN2C (7%), FAM (15.4%), kit (23.1%); MLL (30.7%), MTAP (loss 30.7%,) NF1 (30.7%), NOTCH (23.1%), PDGFRA (26.9%), RB1 (23.1%), tp53 (53.8%). PTEN alteration was present in 13 patients with 3 of them with 2 alterations. EGFR was found with more than 1 alteration in 5 patients: 10 amplifications, 2 rearrangements, 6 deletion and 14 other mutation. Finally, we identified also: 1 patient with a mutation of RET, 2 patients with non-actionable NTRK mutations, 3 MDM2 mutated patients. Two patients with an FGFR alteration underwent a treatment with Erdafitinib. In the LGG group we identified 11 patients, 7 females, with a medium age of 34 years old; median OS was 116.8 months/ 9.6 years (CI 95% 45.8-187.8). All patients were IDH mutated, 2 of them with a IDH2 alteration. 1p19q codeletion was detected in 3 patients with 5 unknown; 1 patent was found to have an MGMT methylation, 8 were not tested. A total of 81 mutations were identified with the most frequent: ATRX (54.5%), CDKN2A (18.1%), EGFR (36.4%) with 2 amplifications and 2 rearrangement; TERT (36.4%), tp53 (54.4%), TSC, NOTCH and PTEN loss in 27.7%. One of the patient has a TMB high (117) and he received immunotherapy in a clinical trial. Each of thr 36 patients had at least 6 mutations. We don’t know the percentage of patients who underwent a molecular profile without any alteration founded. Targetable drivers with a clinical relevance were: FGFR, NTRK, ALK, PTEN, MDM2, CDKN2A and CDKN2B. Conclusions: Molecular profiling gives an important data collection and therapeutic options on poor prognostic tumors such as GBM and LGG and may lead to explore new pathways of innovations.
Assessing PD-L1 without a biopsy and through PD-L1 PET imaging with 18F-BMS-986229.
Authors: Michael A. Postow, Audrey Mauguen, Denise Frosina, Achim A. Jungbluth, Klaus J. Busam, Neeta Pandit-Taskar
Journal: Journal of Clinical Oncology (2022)

2578 Background: Programmed death ligand-1 (PD-L1) is usually determined by immunohistochemistry (IHC). Determining PD-L1 status by whole body, non-invasive PD-L1 PET imaging with 18F-BMS-986229 tracer infusion may be a way to circumvent limitations to PD-L1 IHC such as poor tissue availability; discrepant PD-L1 IHC results among different tumors within the same patient; and inability to measure PD-L1 longitudinally given challenges with repeated biopsies. Methods: Within the prospective ADAPT-IT trial (NCT03122522) testing an abbreviated course of nivolumab (nivo) + ipilimumab (ipi) in patients with unresectable stage III or IV melanoma, we investigated PD-L1 PET imaging in a 10-patient expansion cohort at baseline and after 6 weeks of treatment. Maximum standard uptake value (SUV max) and mean of all SUV max for lesions for PD-L1 PET were calculated on a whole patient level for each target/ non target lesion. Standard treatment response was determined by RECIST v1.1 at weeks 6 and 12. PD-L1 IHC was scored using the E1L3N antibody by tumor proportion score (TPS), Immune Cell Score (ICS), and a Combined Positive Score (CPS). Comparisons between PD-L1 PET parameters and response were determined by complete or partial response (CR/PR); stable disease (SD), and progressive disease (PD) at respective imaging timepoints. Absolute changes in PD-L1 SUV mean and max were calculated between scans. The correlation between PD-L1 PET and IHC was estimated using Spearman’s coefficient correlation. Results: Five patients (50%) had a PR to treatment at week 6; one of these PR became a CR at week 12 and one PR was not assessable at week 12. All RECIST responders at week 6 (n = 5) had baseline PD-L1 SUV mean ≥3.00, and all progressors at week 6 (n = 3) had baseline PD-L1 SUV mean ≤2.60 (Table). A similar trend was observed when assessing response at week 12 and when considering baseline PD-L1 SUV max. Patients had changes in their PD-L1 SUV levels between baseline and week 6. Baseline PD-L1 SUV mean (inclusive of all lesions within a patient) correlated with PD-L1 IHC by TPS, ICS, and CPS (r = 0.64, 0.5, 0.47, respectively). No patients had side effects from 18F-BMS-986229 tracer infusion. Conclusions: The signal of PD-L1 positivity by PET imaging with 18F-BMS-986229 at baseline appears associated with early efficacy from nivo + ipi in this small cohort and may offer additional information than PD-L1 IHC. The ability to assess PD-L1 on a whole patient level at multiple timepoints on treatment may have future implications in how best to sequence and combine immunotherapies but further study in larger patient cohorts is needed. Clinical trial information: NCT03122522. [Table: see text]
Seroconversion following first and second dose of COVID-19 vaccination among cancer patients: A prospective longitudinal observational study from India on the effectiveness of COVID vaccines.
Authors: Krishnamani Iyer Kalpathi, Raj Kishore Pappala, Ayesha Nawaz, Mithra Krishnamani, Kavita Mathi
Journal: Journal of Clinical Oncology (2022)

e13629 Background: Cancer patients are at high risk of infections and vaccination against SARS CoV-2 virus is essential to reduce the risk of COVID-19 and its complications. Different types of vaccines against SARS CoV-2 have been developed at record speed, followed by emerging efficacy studies of these vaccines. Our aim is to assess the efficacy of these vaccines in Indian cancer patients, along with factors such as intervals between doses impacting a robust immune response. Methods: A longitudinal observational study was done to evaluate the seroconversion post one and/or two doses of ChAdOx1 nCoV-19 (Covishield) and BBV152 (Covaxin) vaccine in adult cancer patients. Patients received 0.5 ml of vaccine 4 – 12 weeks apart based on existing Government regulations. A minimum gap of four weeks post vaccination for sample collection was followed. Samples were collected during patient follow up or treatment schedules. The control group comprised of healthy volunteers. Our primary endpoint was to assess seroconversion rates to SARS COV-2 spike protein after first and/or second dose. Our secondary endpoint was to explore the factors influencing seroconversion and to compare the two available vaccines in India, Covishield and Covaxin. Results: Between May 1, 2021 and January 16, 2022, antibody levels were measured in 219 patients after second dose and 56 patients after each dose. The mean age was 57.6+12.2 years (24-85 years) with 52% above 60 years age, and 68% being women. Most common cancer was breast (39.3%) followed by GIT (17.4%), while 44% had metastatic disease. Overall, 54.3% had not received any systemic therapy in the past 6 months, while 22.4% had received chemotherapy and 14.2% had received biologics. Three fourth of the patients had received Covishield and the rest Covaxin. Amongst the 56 patients who had antibody testing after both doses, seroconversion after first and second dose were 85.7% and 96.4% respectively. Higher seroconversion was seen in younger age group, treated with biologics without chemotherapy. In 219 patients, post second dose, seroconversion was marginally higher in women compared to men (96.6% vs 91.4%), on biologics (96.8%) when compared to patients taking chemotherapy (89.8 %), although not statistically significant. Overall patients on Covishield vaccine showed higher seroconversion, compared to Covaxin (P = 0.002) (OR- 5.9). Timing of antibody sample had no effect on seroconversion. Conclusions: Both Covishield and Covaxin are immunogenic in cancer patients. Seroconverison after first and second doses were 85.7% and 96.4%with higher rates amongst patients on biologics compared to chemotherapy. We are hoping to continue our study longitudinally to further explore factors impacting efficacy amongst these two vaccines.
Comparison of the checkpoint inhibitor pneumonitis incidence between immunotherapy alone or in combination with chemotherapy for lung cancer: An observational, retrospective pharmacovigilance study.
Authors: Pei-Hang Xu, Yi-Fan Zheng, Zi-mu Li, Yu-Kun Kuang, Ke-Jing Tang
Journal: Journal of Clinical Oncology (2022)

2655 Background: Clinical trials lack direct cross-comparison in safety between immune checkpoint inhibitor (ICI) as monotherapy and in combination with chemotherapy. The adverse event of checkpoint inhibitor pneumonitis (CIP) is an important factor influencing the treatment decision making. We performed a real-world pharmacovigilance study in the US Food and Drug Administration Adverse Event Reporting System (FAERS) to determine if ICI combination therapy is superior to monotherapy for lung cancer patients in terms of CIP incidence. Methods: The database of lung cancer patients receiving ICI between 2015 and 2020 was extracted for this study. The strategy-specific durations of the pneumonitis event were compared using the Kaplan-Meier method. Reporting odds ratio (ROR), a surrogate measure in disproportionality analysis, was used to assess the signal of CIP between ICI treatment strategies. Results: A total of 27,882 lung cancer patients with reported adverse events were involved. Among them, 1763 (6.3%) CIP after ICIs therapy were identified. In general, ICI usage was associated with over-reporting frequencies of CIP, but this association was no longer significant after adjustment (ROR: 1.14, 95%CI 0.86-1.49). The median times to CIP occurred early after therapy onset, either in ICI monotherapy or in combination with chemotherapy (41 days and 37 days, log-rank p&gt;0.05). Different reporting frequencies emerged when we further compared different ICI strategies. Combination therapy with anti-PD-1 and chemotherapy was associated with a higher CIP incidence compared with anti-PD-1 monotherapy (ROR: 1.86, 95%CI 1.37-2.51), whereas anti-PD-L1/ CTLA-4 medications had lower risks in combination with chemotherapy (ROR: 0.31, 95%CI 0.16-0.56 and ROR: 0.41, 95%CI 0.09-1.22). Subgroup analyses on those with recorded therapy duration also indicated that reports of CIP were significantly lower with combination therapy of PD-L1 and CTLA-4 (ROR: 0.52, 95%CI 0.36-0.74 and ROR: 0.22, 95%CI 0.09-0.51 respectively). Conclusions: Compared with ICI monotherapy, the combination with chemotherapy might have an acceptable risk of CIP. Anti-PD-1 medications with additional chemotherapy could increase the risk of pneumonitis, whereas the risk was lower in the combination strategy with anti-PD-L1/CTLA-4. The combination might be a better therapeutic strategy than ICI monotherapy in treating lung cancer, regarding the CIP incidence. [Table: see text]
Pneumonitis in immunotherapy alone vs. chemoimmunotherapy: A systematic review and meta-analysis.
Authors: Alexander Michael Barbaro, Matthew Siskin, Cassandra Grello, Adrian V Hernandez, Jared Dublin, Sean Breslin, Salman Rafi Punekar, Vamsidhar Velcheti
Journal: Journal of Clinical Oncology (2022)

e21120 Background: Immune checkpoint inhibitors (ICIs) are commonly used in the treatment of non-small cell lung cancer (NSCLC), and are given alone or in combination with cytotoxic chemotherapy. These agents are sometimes associated with immune related adverse events (irAEs). Pneumonitis in particular is a common and sometimes life-threatening complication of treatment with ICIs, especially in lung cancer patients. Chemotherapy is known to cause immune suppression and deplete T cell populations, and might be expected to attenuate the incidence or severity of irAEs when given with ICIs. To date, few studies explore this possibility. This meta-analysis compared the incidence of any grade and severe (grade ≥3) pneumonitis in patients who received ICIs alone vs. combination ICI + chemotherapy for the treatment of advanced NSCLC. Methods: Embase and PubMed databases were searched through May 2021 for clinical trials investigating the use of ICIs for treatment of advanced NSCLC alone and/or in combination with chemotherapy. Interventions were categorized into ICI alone vs. ICI + chemotherapy and rates of any grade and severe (grade ≥3) pneumonitis for patients in each category were collected. The incidence of these events across interventions was aggregated using inverse variance weighting, and rates among patients who received ICI alone and ICI + chemotherapy were compared. Results: 1929 studies were identified by the initial search, of which 36 met inclusion criteria. From these, 24 interventional arms using ICIs alone (total patients n = 11,163) and 12 using combination therapy (n = 4,129) were identified and analyzed. ICIs included agents targeting PD1 (n = 22), PD-L1 (n = 11), CTLA-4 (n = 1), and the combination of CTLA-4 with PD1 or PD-L1 (n = 2). Rates of any grade pneumonitis did not differ significantly between patients who received ICI alone vs combination therapy (0.03; 95% CI 0.02-0.04 vs 0.04; 95% CI 0.02-0.08; P = 0.5). Rates of severe pneumonitis also did not differ between groups (0.01; 95% CI 0.01-0.02 vs 0.01; 95% CI 0.00 – 0.02; P = 0.5). Conclusions: No difference was found in the rates of any grade or severe pneumonitis between patients who received ICI alone vs. ICI + chemotherapy.
Sensitive detection of cancer using deep learning model of cfDNA genome-wide methylation data.
Authors: Wan Kim, Minjung Kim, Juntae Park, Sook Ryun Park, Bo Hyun Kim, Jeong-Won Lee, Dongryul Oh, Ki Byung Song, Eunsung Jun, Ju Hyun Shim, Danbi Lee, Choi Jonggi, Changhoon Yoo, Tae-Rim Lee, Jin Mo Ahn, Junnam Lee, Dasom Kim, Chang Seok Ki, Eunhae Cho
Journal: Journal of Clinical Oncology (2022)

e18789 Background: Methylation analysis of cfDNA has been used to diagnose cancer in its early stages. Previous research has concentrated on local methylation signals using cancer type specific methylation markers. We used not just methylation markers, but also global methylation patterns for sensitive cancer detection. Methods: We generated methylation data from cancer patients (N = 717) and normal controls (N = 190) using cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq, N = 907) and cell free whole genome enzymatic methyl seq (cfWGEM-seq, N = 162) from cancer patients (N = 137) and normal controls (N = 25). We analyzed at the Illumina 450K methylation microarray (N = 3,479) from The Cancer Genome Atlas (TCGA) to find differentially methylated regions (DMR) in 6 cancer types (breast, lung, liver, ovarian, esophageal, and pancreatic cancer). After determining the overlapping DMRs of each dataset, the best 1661 regions that differed the most between the cancer patient group and the normal group were left. The selected marker-based model was cross-validated using cfMeDIP samples separated into training, validation, and test sets. Additionally, global methylation count values of cfMeDIP-seq data were used to train convolutional neural network. Finally, the global methylation pattern deep learning algorithm and the marker-based algorithm were combined to detect cancer. Results: Deep learning models based on selected markers and global methylation patterns achieved test data accuracy of 0.88-0.92 and 0.90-0.91, respectively, with AUC 0.94-0.96 and 0.95-0.96. The ensemble model of two models showed test data accuracy 0.91-0.92 and AUC 0.96-0.97 with the detection of early stage of cancers (stage 1:detection rate of 88-100%, stage 2:detection rate of 75-100%, stage 3:detection rate of 90-97%, stage 4:detection rate of 92-100%). Conclusions: In this study, we selected best markers by using tissue methylation dataset (TCGA) and cfDNA methylation datasets (cfMeDIP-seq, cfWGEM-seq). To train cancer detection models, we used not only the DMR pattern but also the global methylation pattern. And the ensemble model that included these features outperformed a single model. In the field of early cancer detection, our models show potential.